Logistic Model Training Task

A Logistic Model Training Task is a supervised model-based classification task whose classification function family is a logistic function.

• Context:
  • Input: a Logistic Regression Model.
  • output: a Fitted Logistic Function.
  • It can be solved by a Logistic Regression System (that implements an LR algorithm).* Counter-Example(s)
  • It can (typically) assumes that the Log-Odds of an observation y can be expressed as a linear function of the input variables.
• Example(s)
  • use logistic regression to solve the Iris Dataset Classification Task.
  • ...
• Counter-Example(s)
  • a Classification Tree Training Task.
  • an SVM Training Task.
  • a Neural Network Training Task.
• See: Linear Regression Task.

References

1997

• (Magder & Hughes, 1997) ⇒ Laurence S. Magder, and James P. Hughes. (1997). "Logistic Regression When the Outcome is Measured with Uncertainty." American journal of epidemiology 146, no. 2
  • QUOTE: ... Epidemiologists often use logistic regression to estimate the effect of various predictors on some binary outcome of interest ...

• Concept